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People in today's environment rely more on the web news because it is more readily available to them. Internet usage is increasing daily, which contributes to the dissemination of false information. Similar bogus news can spread intentionally or by accident, but it still has an impact on society. Accordingly, an expanding number of fake news must be constrained by involving the computational instrument which predicts similar deceptive data as though it's phony or genuine. The objective is to concentrate on developing computational tool which helps in classifying news using Naive Bayes algorithm. Multinomial language processing is used to classify fake news in secure manner. It helps to identify the fake news. It gives topmost perfection and assists with deciding the fake news. To descry fake news, proper dataset that has predefined set of classified news is required to process the data further. Stemming or …